Penerapan Algoritma Local Binary Pattern untuk Pengenalan Pola Sidik Jari


  • Nurul Hayaty Universitas Maritim Raja Ali Haji
  • Martaleli Bettiza Universitas Maritim Raja Ali Haji
  • Eko Imam Pratama Universitas Maritim Raja Ali Haji



local binary pattern, fingerprint, manhattan distance


Recognition of patterns in a person by using parts of the human body, such as on fingerprints, has been widely applied in life such as to perform absenteeism, tracking a criminal, system security and so on. Local Binary Pattern (LBP) algorithm is known as an algorithm that can describe local texture pattern in an area. LBP uses 8 scattered circular neighborhoods with center pixels centered. In a 3 x 3 pixel image, the binary value in the image center is compared with the surrounding value. The surrounding value will be 1 if the central pixel value is smaller, and is 0 if the central binary value is greater. A total of 78 data were used for this study where 26 data were using blue ink fingerprints, and 26 black ink data. After the fingerprint pattern data obtained then the image is scanned. After that the image in the crop to be 50 pixels x 50 pixels, so all the data becomes uniform. The algorithm used to make an introduction is the Manhattan Distance algorithm. Based on the test results of 26 test data with different color inks, the result obtained accuracy of 61.54%.


Download data is not yet available.




How to Cite

N. Hayaty, M. Bettiza, and E. I. Pratama, “Penerapan Algoritma Local Binary Pattern untuk Pengenalan Pola Sidik Jari”, sustainable, vol. 6, no. 2, pp. 74–79, Oct. 2017.